"""simple docstring"""


from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional

from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand


try:
	from fastapi import Body, FastAPI, HTTPException
	from fastapi.routing import APIRoute
	from pydantic import BaseModel
	from starlette.responses import JSONResponse
	from uvicorn import run

	a				=True
except (ImportError, AttributeError):
	a				=object





	def      lowerCamelCase_					(   *__lowerCAmelCase  ,       **__lowerCAmelCase							)				->   Any:




							'''simple docstring'''



							pass





	a				=False


a				=logging.get_logger('transformers-cli/serving')





def      lowerCamelCase_					(   __lowerCAmelCase							)				->   List[str]:




						'''simple docstring'''



						lowerCamelCase__   =pipeline(
						    task=args.task  ,       model=args.model if args.model else None  ,       config=args.config  ,       tokenizer=args.tokenizer  ,       device=args.device  ,       )
						return ServeCommand(__lowerCAmelCase  ,       args.host  ,       args.port  ,       args.workers							)






class   __UpperCAmelCase		(      __lowerCAmelCase      ):
				A__ :  dict






class   __UpperCAmelCase		(      __lowerCAmelCase      ):
				A__ :  List[str]
				A__ :  Optional[List[int]]






class   __UpperCAmelCase		(      __lowerCAmelCase      ):
				A__ :  str






class   __UpperCAmelCase		(      __lowerCAmelCase      ):
				A__ :  Any






class   __UpperCAmelCase		(      __lowerCAmelCase      ):

				@staticmethod
				def 						_a      ( _lowerCamelCase ):
										lowerCamelCase__   =parser.add_parser(
										    "serve"      ,					help="CLI tool to run inference requests through REST and GraphQL endpoints." )
										serve_parser.add_argument(
										    "--task"      ,					type=_lowerCamelCase      ,					choices=get_supported_tasks()      ,					help="The task to run the pipeline on"      ,					)
										serve_parser.add_argument("--host"      ,					type=_lowerCamelCase      ,					default="localhost"      ,					help="Interface the server will listen on." )
										serve_parser.add_argument("--port"      ,					type=_lowerCamelCase      ,					default=8888      ,					help="Port the serving will listen to." )
										serve_parser.add_argument("--workers"      ,					type=_lowerCamelCase      ,					default=1      ,					help="Number of http workers" )
										serve_parser.add_argument("--model"      ,					type=_lowerCamelCase      ,					help="Model's name or path to stored model." )
										serve_parser.add_argument("--config"      ,					type=_lowerCamelCase      ,					help="Model's config name or path to stored model." )
										serve_parser.add_argument("--tokenizer"      ,					type=_lowerCamelCase      ,					help="Tokenizer name to use." )
										serve_parser.add_argument(
										    "--device"      ,					type=_lowerCamelCase      ,					default=-1      ,					help="Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)"      ,					)
										serve_parser.set_defaults(func=_lowerCamelCase )

				def __init__( self      ,					_lowerCamelCase      ,					_lowerCamelCase      ,					_lowerCamelCase      ,					_lowerCamelCase ):
										lowerCamelCase__   =pipeline

										lowerCamelCase__   =host
										lowerCamelCase__   =port
										lowerCamelCase__   =workers

										if not _serve_dependencies_installed:
																raise RuntimeError(
																    "Using serve command requires FastAPI and uvicorn. "
																    "Please install transformers with [serving]: pip install \"transformers[serving]\"."
																    "Or install FastAPI and uvicorn separately." )
										else:
																logger.info(F'''Serving model over {host}:{port}''' )
																lowerCamelCase__   =FastAPI(
																    routes=[
																        APIRoute(
																            "/"      ,					self.model_info      ,					response_model=_lowerCamelCase      ,					response_class=_lowerCamelCase      ,					methods=["GET"]      ,					),
																        APIRoute(
																            "/tokenize"      ,					self.tokenize      ,					response_model=_lowerCamelCase      ,					response_class=_lowerCamelCase      ,					methods=["POST"]      ,					),
																        APIRoute(
																            "/detokenize"      ,					self.detokenize      ,					response_model=_lowerCamelCase      ,					response_class=_lowerCamelCase      ,					methods=["POST"]      ,					),
																        APIRoute(
																            "/forward"      ,					self.forward      ,					response_model=_lowerCamelCase      ,					response_class=_lowerCamelCase      ,					methods=["POST"]      ,					),
																    ]      ,					timeout=600      ,					)

				def 						_a      ( self ):
										run(self._app      ,					host=self.host      ,					port=self.port      ,					workers=self.workers )

				def 						_a      ( self ):
										return ServeModelInfoResult(infos=vars(self._pipeline.model.config ) )

				def 						_a      ( self      ,					_lowerCamelCase = Body(_lowerCamelCase      ,					embed=_lowerCamelCase )      ,					_lowerCamelCase = Body(_lowerCamelCase      ,					embed=_lowerCamelCase ) ):
										try:
																lowerCamelCase__   =self._pipeline.tokenizer.tokenize(_lowerCamelCase )

																if return_ids:
																						lowerCamelCase__   =self._pipeline.tokenizer.convert_tokens_to_ids(_lowerCamelCase )
																						return ServeTokenizeResult(tokens=_lowerCamelCase      ,					tokens_ids=_lowerCamelCase )
																else:
																						return ServeTokenizeResult(tokens=_lowerCamelCase )

										except Exception as e:
																raise HTTPException(status_code=500      ,					detail={"model": "", "error": str(_lowerCamelCase )} )

				def 						_a      ( self      ,					_lowerCamelCase = Body(_lowerCamelCase      ,					embed=_lowerCamelCase )      ,					_lowerCamelCase = Body(_lowerCamelCase      ,					embed=_lowerCamelCase )      ,					_lowerCamelCase = Body(_lowerCamelCase      ,					embed=_lowerCamelCase )      ,					):
										try:
																lowerCamelCase__   =self._pipeline.tokenizer.decode(_lowerCamelCase      ,					_lowerCamelCase      ,					_lowerCamelCase )
																return ServeDeTokenizeResult(model=""      ,					text=_lowerCamelCase )
										except Exception as e:
																raise HTTPException(status_code=500      ,					detail={"model": "", "error": str(_lowerCamelCase )} )






				async def 						_a      ( self      ,					_lowerCamelCase=Body(_lowerCamelCase      ,					embed=_lowerCamelCase ) ):

										# Check we don't have empty string
										if len(_lowerCamelCase ) == 0:
																return ServeForwardResult(output=[]      ,					attention=[] )

										try:
																# Forward through the model
																lowerCamelCase__   =self._pipeline(_lowerCamelCase )
																return ServeForwardResult(output=_lowerCamelCase )
										except Exception as e:
																raise HTTPException(500      ,					{"error": str(_lowerCamelCase )} )



"""simple docstring"""


import random





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase = False							)				->   dict:




						'''simple docstring'''



						lowerCamelCase__   ={i: [] for i in range(__lowerCAmelCase							)}

						# if probability is greater or equal than 1, then generate a complete graph
						if probability >= 1:
												return complete_graph(__lowerCAmelCase							)
						# if probability is lower or equal than 0, then return a graph without edges
						if probability <= 0:
												return graph

						# for each couple of nodes, add an edge from u to v
						# if the number randomly generated is greater than probability probability
						for i in range(__lowerCAmelCase							):
												for j in range(i + 1  ,       __lowerCAmelCase							):
																		if random.random() < probability:
																								graph[i].append(__lowerCAmelCase							)
																								if not directed:
																														# if the graph is undirected, add an edge in from j to i, either
																														graph[j].append(__lowerCAmelCase							)
						return graph





def      lowerCamelCase_					(   __lowerCAmelCase							)				->   dict:




						'''simple docstring'''



						return {
						    i: [j for j in range(__lowerCAmelCase							) if i != j] for i in range(__lowerCAmelCase							)
						}


if __name__ == "__main__":
	import doctest

	doctest.testmod()


